Descriptive and Inferential Statistics Descriptive and inferential statistics are incredibly similar forms of research testing within psychology. Each seeks to analyze, describe, and possibly predict a population’s behavior. As with psychology itself, statistical analysis within psychology began as a philosophy (Goodwin, 2008). This philosophy quickly turned to a scientific pursuit, again mirroring psychology itself. A person observes, and wonders why that event occurred. That person makes a guess, known as forming a hypothesis, then he or she observes the situation again making small changes to test the theory. Once the determination that the behavior or occurrence is prevalent in a population for which the statistical study is relevant it is given a level of probability (A. Aron, E. Aron, & Coups, 2009). Statistics has two branches descriptive and inferential, and both branches use fundamental concepts as measurements of predictability. The predictability or probability of an event or behavior is determined through values, variables, and scores. Statistics would be redundant if data given by considerable surveys’ and testing were simple to interpret. However, the mass of information concerning a sample of a parameter used in inferential statistics, and a parameter used in descriptive statistics has become the easiest known way to interpret data (University of California, 1998). Expressed differently, raw data are difficult to visualize and translate into descriptive or inferential statistics (Leard Statistics, 2010). Properly interpreting data and graphing it in an easily understandable truthful manner is the major function in descriptive and inferential statistics. Descriptive Statistics Descriptive statistics summarize numbers in a set of data, such as mean or median, and values, or scores (A. Aron, E. Aron, &...

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